The Combined Method of Classification for Improvement of Intrusion Detection System in Computer Networks

The objective of an intrusion detection system, is classifying activities into two major categories including: normal and attack. This paper is using one of the algorithm classification methods called Adaboost through applying the necessary changes to increase the efficiency of the algorithm in order to detect attacks. The first change was the weight of initial sample of Adaboost algorithm. According to the asymmetric distribution of data it causes some classes not to teach properly. The first change was the algorithm Adaboost in order to initialize the weight of the samples; rather instead of bearing the equal weight into all of the samples the probability of the primary selection of all the samples for learning the algorithms is equal together.